The agent assembled a comprehensive overview of Linq by combining fetched homepage/API landing pages, documentation, and web search results. The site successfully conveyed what Linq does, who it's for, and key differentiators, but pricing details were inaccessible in static HTML (step [11] pricing page is JavaScript-rendered), forcing reliance on third-party sources and prior knowledge. The agent satisfied the core task but had to work around dynamic content and incomplete public pricing transparency.

• ›Step [1] (homepage) and [3] (iMessage API page) provided core positioning and feature list via meta tags and SEO content, clearly stating 'iMessage, RCS, SMS, and Voice' and '99.95% uptime, no per-message pricing.' These were content-bearing and directly used in the final answer.
• ›Step [4] (API docs homepage) confirmed technical positioning for developers but required JavaScript rendering to surface detailed API capabilities; agent noted inability to see full content.
• ›Step [11] (pricing page) returned only a React shell with no readable pricing tiers in static HTML—a significant navigability gap. Agent explicitly flagged this and noted that third-party sources (~$250/line/month) were unconfirmed by Linq's own site.
• ›Steps [12] (iMessage API providers comparison blog) and search results [10, 16] provided competitive differentiation (vs. Photon, SendBlue, Twilio) but agent could not see full blog content in HTML and relied on web search snippets and prior knowledge to reconstruct the comparison.
• ›Web searches [9, 10, 13–18] were essential discovery paths—agent found official Linq URLs and third-party comparison sites that indexed Linq's claims. Without search, pricing and competitive positioning would have been completely opaque.
• ›Site structure is well-navigable for initial discovery (clear /imessage-api and /s/pricing URLs exist) but accessibility for agents degrades significantly due to JavaScript-heavy rendering of pricing, features, and comparison content. Agent-ready metadata (Twitter cards, meta descriptions) exists but doesn't substitute for machine-readable pricing or feature matrices.